Journal
BRITISH JOURNAL OF GENERAL PRACTICE
Volume 63, Issue 616, Pages E787-E794Publisher
ROYAL COLL GENERAL PRACTITIONERS
DOI: 10.3399/bjgp13X674477
Keywords
antibiotic prescribing; meta-analysis; point-of-care C-reactive protein testing; primary care; respiratory tract infections
Categories
Funding
- National Training Center for General Practice, Ministry of Health China
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Background Most patients with respiratory tract infections (RTIs) are prescribed antibiotics in general practice. However, there is little evidence that antibiotics bring any value to the treatment of most RTIs. Point-of-care C-reactive protein testing may reduce antibiotic prescribing. Aim To systematically review studies that have examined the association between point-of-care (POC) C-reactive protein testing and antibiotic prescribing for RTIs in general practice. Design and setting Systematic review and meta-analysis of randomised controlled trials and observational studies. Method MEDLINE (R) and Embase were systematically searched to identify relevant publications. All studies that examined the association between POC C-reactive protein testing and antibiotic prescribing for patients with RTIs were included. Two authors independently screened the search results and extracted data from eligible studies. Dichotomous measures of outcomes were combined using risk ratios (RRs) with 95% confidence intervals (CIs) either by fixed or random-effect models. Results Thirteen studies containing 10 005 patients met the inclusion criteria. POC C-reactive protein testing was associated with a significant reduction in antibiotic prescribing at the index consultation (RR 0.75, 95% CI = 0.67 to 0.83), but was not associated with antibiotic prescribing at any time during the 28-day follow-up period (RR 0.85, 95% CI = 0.70 to 1.01) or with patient satisfaction (RR 1.07, 95% CI = 0.98 to 1.17). Conclusion POC C-reactive protein testing significantly reduced antibiotic prescribing at the index consultation for patients with RTIs. Further studies are needed to analyse the confounders that lead to the heterogeneity.
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